Abstract:
Methods and apparatus for multiplexing reference signals for Multiple Input Multiple Output (MIMO) layers are provided. Resources for Demodulation Reference Signals (DMRS) corresponding to each of two or more data streams are assigned, wherein the resources assigned to each of the data streams are staggered in frequency and span two or more OFDM (Orthogonal Frequency Divisional Multiplexing) symbols. The DMRS is transmitted using the assigned resources.
Abstract:
The connection management entity apparatus determines a set of modems within coverage of a particular area. Each modem of the set of modems is associated with a particular aircraft and one carrier of a plurality of carriers. The apparatus allocates subsets of modems to each eNB of a set of eNBs. The allocation allows each eNB to communicate with the allocated subset of modems. Each eNB operates on a different carrier. The apparatus may be a eNB. The eNB determines a set of modems within coverage of the eNB. The set of modems is associated with one carrier of a plurality of carriers. The eNB operates on the one carrier. Each modem in the set of modems is associated with a different aircraft. The eNB sends information indicating the set of modems and receives an allocation of a second set of modems in response to the sent information.
Abstract:
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive a generative channel model (GCM) that outputs channel information pertaining to a digital twin (DT). The UE may receive a configuration of a downlink reference signal. The UE may perform channel estimation using the configuration of the downlink reference signal. The UE may transmit a report, wherein the report includes a precoding indicator, and wherein at least one of computation of the precoding indicator, or a channel estimation algorithm for the channel estimation, uses the GCM. Numerous other aspects are described.
Abstract:
Certain aspects of the present disclosure provide techniques for configuring a user equipment (UE) with machine learning models based on compute resource limits for the UE. An example method generally includes generating a set of machine learning models for use in a wireless communications device based on one or more compute resource limits associated with a type of the wireless communications device; and deploying the generated set of machine learning models.
Abstract:
A positioning reference signal measurement method includes: receiving, at a user equipment from a network entity, an OFDM PRS (orthogonal frequency division multiplexing positioning reference signal) comprising a first set of first OFDM symbols that are consecutive and include a first center symbol and at least one pair of first side symbols disposed symmetrically about the first center symbol and having identical resource element sounding patterns; combining the first side symbols in each of the at least one pair of first side symbols to produce at least one first combined symbol; and determining a measurement of the OFDM PRS based on the at least one first combined symbol and the first center symbol.
Abstract:
In an aspect, a wireless node may determine a sub-panel configuration associated with a reconfigurable intelligence surface (RIS) that includes a plurality of sub-panels. The wireless node may transmit or receive one or more signals via one or more sub-panels of the plurality of sub-panels in accordance with the sub-panel configuration.
Abstract:
In an aspect, a UE obtains information (e.g., UE-specific information, etc.) associated with a set of triggering criteria for a set of neural network functions, the set of neural network functions configured to facilitate positioning measurement feature processing at the UE, the set of neural network functions being generated dynamically based on machine-learning associated with one or more historical measurement procedure, obtains positioning measurement data associated with a location of the UE, and determines a positioning estimate for the UE based at least in part upon the positioning measurement data and at least one neural network function from the set of neural network functions that is triggered by at least one triggering criterion from the set of triggering criteria.
Abstract:
Some aspects described herein relate to receiving, from each of multiple UEs in sidelink communications, a report of a model update for a federated learning model, generating, based on one or more parameters in the report of the model update received from each of the multiple UEs, a converged model update, and transmitting, to an upstream node, the converged model update. Other aspects relate to receiving, from a base station, an indication of a federated learning model, generating, for the federated learning model and based on a local training on the federated learning model, a model update to be applied to the federated learning model, and transmitting, to a relay UE in sidelink communication, a report of the model update.
Abstract:
Certain aspects of the present disclosure generally relate to techniques for selecting a base graph to be used for wireless communications. Selection can be based on a variety of factors. A base graph can be used to derive a low-density parity-check (LDPC) code used for encoding a retransmission of an original transmission. An exemplary method generally includes selecting, based on a modulation and coding scheme (MCS) and a resource allocation (RA) for transmitting a codeword, a base graph (BG), from which to derive a low density parity check (LDPC) code for use in encoding data bits in the codeword (e.g., encoding data bits of a bitstream such that some redundant bits are included in the codeword), encoding the data bits to generate the codeword using the LDPC code derived from the selected BG, and transmitting the codeword using the MCS via resources of the RA.
Abstract:
Disclosed are techniques for wireless communication. In an aspect, a user equipment (UE) applies a plurality of positioning reference signal (PRS) processing windows to a PRS resource received from a network node over a multipath channel, determines a plurality of channel estimates for the PRS resource based on the plurality of PRS processing windows, and determines a plurality of positioning measurements of the PRS resource based on the plurality of channel estimates.